Deep Learning Genome-wide Linkage Association Study for Wheat Fusarium Head Blight Resistance Genes Discovery

Background: Fusarium head blight (FHB) is one of the most devastating diseases of wheat worldwide and artificial intelligence can assist with understanding resistance to the disease. Considering different sample populations, marker types, reference maps, and statistical methods, we developed a Deep Learning Genome-wide Linkage Association Study (dpGLAS) of FHB resistance in wheat. Results: The dpGLAS was first applied to two bi-parental population datasets in which the cultivar AC Barrie was a common parent for FHB resistance. Eight candidate gene markers were discovered in the one AC Barrie population and 10 in the other associated with FHB resistance. Eight of these markers were also supported by the conventional QTL mapping. Most of these candidate marker genes were found associated with the Reactive Oxygen Species (ROS) and Abscisic acid (ABA) axes. These ROS and ABA pathways were further supported by RNA-seq transcriptome data of FHB resistant cv. AAC Tenacious, a parent of the third bi-parental population. In this dataset, the ROS-centered Panther protein families were significantly enriched in those genes that had most different response to FHB when compared the resistance Tenacious and the susceptible Roblin. Conclusions: This study developed the framework of dpGLAS and identified candidate genes for FHB resistance in the Canadian spring wheat cultivars AC Barrie and AAC Tenacious.

Genetic epidemiology of depression in the molecular era

Familial aggregation of major depressive disorder has been well established, but identification of specific genetic markers underlying this condition has been challenging. The aims of this chapter are to: (1) provide an overview of the results of twin, family, and adoption studies, which have demonstrated that both genetic and environmental factors contribute to the aetiology of depression; (2) discuss studies of depression in the molecular genetics era, including linkage, association, genome-wide association, sequencing, polygenic, and pharmacogenetic studies; and (3) review challenges in identifying genetic factors underlying depression. The next phase of research in the genetic epidemiology of depression will require integration of research on genetic and environmental risk factors and increased recognition of the role of biologic and genetic vulnerability factors for depression.

Association

Association is the only concept in cognition that is as general, simple, and useful as classic theories in physics. Aristotle claimed that sensory-based events were the elementary units of memory. Such memories then became linked together through learning. The process of linkage—association—led to a powerful, creative computational structure. The ability to form networks of associations was unique to humans. William James extended Aristotle’s ideas by proposing a cognitive system that moved well beyond rote linkage in power and flexibility. Some of the mechanics of associative memory can be explained by synaptic change mechanisms such as the correlational Hebb synapse. Also discussed are examples of the problems caused by a “too good” memory along with use of associative memory aids like mnemonics.

Genetics of drug dependence

Drug-dependence disorders (we focus here on cocaine, opioid, and nicotine dependence) are genetically influenced. Risk genes have been located based primarily on genetic linkage studies, and identified primarily based on genetic association studies. In this article we review salient results from linkage, association, and genome-wide association study methodologies, and discuss future prospects for risk allele identification based on these, and on newer, methodologies. Although considerable progress has been made, it is likely that the application of more extensive sequencing than has previously been practical will be required to identify a fuller range of risk variants.